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Catalyzing Informed Residential Energy Retrofit Decisions via Domain-Specific LLM

arXiv:2602.20181v2 Announce Type: replace-cross Abstract: Residential energy retrofit initiation is often stalled by an expertise gap, where homeowners lack the technical literacy required for structu

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Research

Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?

DGX agent

arXiv:2502.07963v4 Announce Type: replace-cross Abstract: Medical research faces well-documented challenges in translating novel treatments into clinical practice. Publishing incentives encourage rese

researcharxiv-cs-ai

23 Apr 2026

Causal-Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury

arXiv:2604.20259v1 Announce Type: new Abstract: Accurate early prediction of Acute Kidney Injury (AKI) is critical for timely clinical intervention. However, existing deep learning models struggle wit

CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs

model-releasesarxiv-cs-cv

arXiv:2604.20460v1 Announce Type: new Abstract: Safety-critical traffic reasoning requires contrastive consistency: models must detect true hazards when an accident occurs, and reliably reject plausib

Local Ai

CEDAR: Context Engineering for Agentic Data Science

arXiv:2601.06606v2 Announce Type: replace-cross Abstract: We demonstrate CEDAR, an application for automating data science (DS) tasks with an agentic setup. Solving DS problems with LLMs is an underex

local-aiarxiv-cs-ai

Centering Ecological Goals in Automated Identification of Individual Animals

arXiv:2604.20626v1 Announce Type: cross Abstract: Recognizing individual animals over time is central to many ecological and conservation questions, including estimating abundance, survival, movement,

Chasing the Public Score: User Pressure and Evaluation Exploitation in Coding Agent Workflows

model-releasesarxiv-cs-cl

arXiv:2604.20200v1 Announce Type: new Abstract: Frontier coding agents are increasingly used in workflows where users supervise progress primarily through repeated improvement of a public score, namel

CHASM: Unveiling Covert Advertisements on Chinese Social Media

arXiv:2604.20511v1 Announce Type: cross Abstract: Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements,

applicationsarxiv-cs-ai

Industry

ChatGPT's Nano Banana

This appears to be a Ben's Bites newsletter article discussing ChatGPT's 'Nano Banana' feature or update, likely covering a new capability, model variant, or feature release from OpenAI. Without acces

industryben-s-bites

ChipCraftBrain: Validation-First RTL Generation via Multi-Agent Orchestration

arXiv:2604.19856v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for generating Register-Transfer Level (RTL) code from natural language specifications, but single-shot gene

safetyarxiv-cs-ai

CHORUS: An Agentic Framework for Generating Realistic Deliberation Data

arXiv:2604.20651v1 Announce Type: new Abstract: Understanding the intricate dynamics of online discourse depends on large-scale deliberation data, a resource that remains scarce across interactive web

agentsarxiv-cs-ai

Cisco unveils universal switch for the quantum networking era

Networking technology giant Cisco Systems Inc. today introduced a new networking switch for quantum systems that routes quantum information between computers while preserving quantum state. The Cisco

applicationssiliconangle

Claude Code spend had gotten to $10.95M runrate peak at SemiAnalysis But then Opus 4.7 saved me. More token effecient for tasks, smarter, an…

model-releasesdylan-patel--x

Claude Code spend had gotten to $10.95M runrate peak at SemiAnalysis But then Opus 4.7 saved me. More token effecient for tasks, smarter, and no fast mode. Thank you @AnthropicAI You saved me from ban

Claude is connecting directly to your personal apps like Spotify, Uber Eats, and TurboTax

model-releasesthe-verge-ai

Claude users can access more apps with Anthropic's AI now thanks to new connectors for everything from hiking to grocery shopping. Anthropic already supported connecting numerous work-related apps to

CLIP-RD: Relative Distillation for Efficient CLIP Knowledge Distillation

arXiv:2603.25383v3 Announce Type: replace Abstract: CLIP aligns image and text embeddings via contrastive learning and demonstrates strong zero-shot generalization. Its large-scale architecture requir

safetyarxiv-cs-cv

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values

model-releasesarxiv-cs-cl

arXiv:2509.03740v3 Announce Type: replace-cross Abstract: Vision-language models (VLMs) like CLIP have shown impressive zero-shot and few-shot learning capabilities across diverse applications. Howeve

Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples

arXiv:2604.20824v1 Announce Type: new Abstract: The central problem in biomedical imaging are batch effects: systematic technical variations unrelated to the biological signal of interest. These batch

applicationsarxiv-cs-lg

Cloud agent infrastructure has a lot of moving parts: VM isolation, session persistence, environment provisioning, orchestration, integratio…

Cloud agent infrastructure has a lot of moving parts: VM isolation, session persistence, environment provisioning, orchestration, integrations. Each one is its own engineering challenge. In this post,

agentscognition-ai--x

Cloudsmith, which is building a cloud-native system to manage software artifacts, raised a 72M Series C, following a 23M Series B in 2025 (Natalie Breymeyer/Axios)

Natalie Breymeyer / Axios: Cloudsmith, which is building a cloud-native system to manage software artifacts, raised a 72M Series C, following a 23M Series B in 2025 — Cloudsmith, a platform that prote

applicationstechmeme

Co-Located Tests, Better AI Code: How Test Syntax Structure Affects Foundation Model Code Generation

arXiv:2604.19826v1 Announce Type: cross Abstract: AI coding assistants increasingly generate code alongside tests. How developers structure test code, whether inline with the implementation or in sepa

CoAuthorAI: A Human in the Loop System For Scientific Book Writing

arXiv:2604.19772v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in scientific writing but struggle with book-length tasks, often producing inconsistent structure a

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment

arXiv:2510.18471v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at code generation by learning from vast code corpora, a fundamental semantic gap remains between the

safetyarxiv-cs-ai

Codex settings

Codex settings refers to configuration options and parameters available for OpenAI's Codex model, a machine learning system trained to understand and generate code. This documentation likely covers ho

tutorialsopenai

Coding with Eyes: Visual Feedback Unlocks Reliable GUI Code Generating and Debugging

arXiv:2604.19750v1 Announce Type: cross Abstract: Recent advances in Large Language Model (LLM)-based agents have shown remarkable progress in code generation. However, current agent methods mainly re

Cognis: Context-Aware Memory for Conversational AI Agents

arXiv:2604.19771v1 Announce Type: cross Abstract: LLM agents lack persistent memory, causing conversations to reset each session and preventing personalization over time. We present Lyzr Cognis, a uni

applicationsarxiv-cs-ai

Cognitive Alignment At No Cost: Inducing Human Attention Biases For Interpretable Vision Transformers

arXiv:2604.20027v1 Announce Type: cross Abstract: For state-of-the-art image understanding, Vision Transformers (ViTs) have become the standard architecture but their processing diverges substantially

safetyarxiv-cs-ai

Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training

arXiv:2508.00414v3 Announce Type: replace Abstract: General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence, enabling complex reason

Cold-Start Forecasting of New Product Life-Cycles via Conditional Diffusion Models

arXiv:2604.20370v1 Announce Type: new Abstract: Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This

Local Ai

Colorful Talks with Graphs: Human-Interpretable Graph Encodings for Large Language Models

arXiv:2602.10386v2 Announce Type: replace Abstract: Graph problems are fundamentally challenging for large language models (LLMs). While LLMs excel at processing unstructured text, graph tasks require

local-aiarxiv-cs-lg

Combo-Gait: Unified Transformer Framework for Multi-Modal Gait Recognition and Attribute Analysis

arXiv:2510.10417v2 Announce Type: replace-cross Abstract: Gait recognition is an important biometric for human identification at a distance, particularly under low-resolution or unconstrained environm

tutorialsarxiv-cs-ai

Come join us! https://www.langchain.com/careers

LangChain, an open-source framework for developing applications with large language models, is recruiting new team members as shared by co-founder Harrison Chase on X (Twitter). The careers page invit

agentsharrison-chase--x

come work with us 🚀 everyone here is rlly nice, smart, curious, ships like crazy, and we make great Slack stickers

come work with us 🚀 everyone here is rlly nice, smart, curious, ships like crazy, and we make great Slack stickers I work with some world class people @LangChain! We're hiring for all sorts of roles -

agentsharrison-chase--x

Coming up: Startup spotlight. Stephanie Wong is joined by @LangChain’s co-founder and CEO, @hwchase17. Watch now → https://x.com/i/broadcast…

Harrison Chase, co-founder and CEO of LangChain, appeared in a startup spotlight interview with Stephanie Wong. The discussion likely covered LangChain's development, its applications in AI and langua

agentsharrison-chase--x

Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding

arXiv:2604.19921v1 Announce Type: new Abstract: Negation is a common and important semantic feature in natural language, yet Large Language Models (LLMs) struggle when negation is involved in natural

researcharxiv-cs-cl

COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling

arXiv:2604.20720v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit performance disparities across languages, with naive multilingual fine-tuning frequently degrading performa

Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models

arXiv:2602.12036v2 Announce Type: replace Abstract: Large-scale verifiable prompts underpin the success of Reinforcement Learning with Verifiable Rewards (RLVR), but they contain many uninformative ex

researcharxiv-cs-cl

Computing the Reachability Value of Posterior-Deterministic POMDPs

arXiv:2602.07473v2 Announce Type: replace Abstract: Partially observable Markov decision processes (POMDPs) are a fundamental model for sequential decision-making under uncertainty. However, many veri

Concept Graph Convolutions: Message Passing in the Concept Space

arXiv:2604.20082v1 Announce Type: new Abstract: The trust in the predictions of Graph Neural Networks is limited by their opaque reasoning process. Prior methods have tried to explain graph networks v

ConeSep: Cone-based Robust Noise-Unlearning Compositional Network for Composed Image Retrieval

model-releasesarxiv-cs-cv

arXiv:2604.20358v1 Announce Type: new Abstract: The Composed Image Retrieval (CIR) task provides a flexible retrieval paradigm via a reference image and modification text, but it heavily relies on exp

Confidence-Based Mesh Extraction from 3D Gaussians

arXiv:2603.24725v2 Announce Type: replace Abstract: Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software ra

researcharxiv-cs-cv

Confidently wrong is worse than just wrong. When an AI searches one giant knowledge base for everything, it finds something—and serves it up…

Confidently wrong is worse than just wrong. When an AI searches one giant knowledge base for everything, it finds something—and serves it up like it's the answer. That's not a model problem. That's a

tutorialspinecone--x

Congrats to the ET30 Class of 2026 who just rang the @Nasdaq Closing Bell. 🔔

Jerry Liu congratulated the ET30 Class of 2026 for ringing the Nasdaq closing bell, celebrating what appears to be an achievement by members of an executive or entrepreneurial cohort. The ET30 is like

agentsjerry-liu--x

Local Ai

Construí um sistema de IA com estado persistente (4B como roteador + 9B principal + 9B “subconsciente”) rodando em 2x RTX 3060 — e ele não se comporta como stateless

A developer describes building a persistent-state AI system using Ollama with three models (a 4B router model, a 9B primary model, and a 9B 'subconscious' model) running on dual RTX 3060 GPUs, demonst

local-air-ollama

Construction of a Battery Research Knowledge Graph using a Global Open Catalog

arXiv:2604.20241v1 Announce Type: new Abstract: Battery research is a rapidly growing and highly interdisciplinary field, making it increasingly difficult to track relevant expertise and identify pote

researcharxiv-cs-cl

Context Attribution with Multi-Armed Bandit Optimization

arXiv:2506.19977v2 Announce Type: replace Abstract: Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable a

Continuous Semantic Caching for Low-Cost LLM Serving

arXiv:2604.20021v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become increasingly popular, caching responses so that they can be reused by users with semantically similar queries h

applicationsarxiv-cs-cl

Control Consistency Losses for Diffusion Bridges

arXiv:2512.05070v2 Announce Type: replace-cross Abstract: Simulating the conditioned dynamics of diffusion processes, given their initial and terminal states, is an important but challenging problem i

Convergent Evolution: How Different Language Models Learn Similar Number Representations

arXiv:2604.20817v1 Announce Type: cross Abstract: Language models trained on natural text learn to represent numbers using periodic features with dominant periods at T=2, 5, 10. In this paper, we iden

tutorialsarxiv-cs-ai